In recent years, researches for presuming behavior of a driver from an image provided by photographing the face, etc. of the driver for driving a vehicle such as an automobile, etc., and for performing various controls (concretely, driving support, giving of an alarm, etc.) corresponding to a presuming result are made.
It is effective to specify driver's eyes so as to grasp the behavior of the driver. Therefore, it is important to detect an eye iris or an eye pupil of the driver from the photographed image. At present, it is tried that the ellipse is detected from an image provided by photographing the circumference of the eye and is recognized as the eye iris or the eye pupil of the driver.
In the photographed image, the eye iris and the eye pupil are not necessarily shown as a perfect ellipse, but are shown as an imperfect figure defective in one portion of a contour by partially covering the eye pupil with an eyelid as shown in FIG. 11A and projecting light on the eye pupil as shown in FIG. 11B in a certain case.
Accordingly, in the control of this kind, it is required that the figure (here, the ellipse) to be detected can be restored even when one portion of the contour is defective.
Thus, the generalized Hough transform is known as a method for restoring the figure from one portion of the contour in this way. This is disclosed in, for example, U.S. Pat. No. 5,638,465.
When the figure of a certain shape is detected by using this generalized Hough transform, a template figure of the same shape as the figure to be detected is prepared. Plural characteristic points Pi (i=1 to M, M represents a natural number) showing characters of this template figure are represented by polar coordinate vectors (Ri, αi) with respect to a reference point set in advance. A table for enumerating this polar coordinate vector (Ri, αi) is set as a template.
Ri is a distance from a reference point, and αi is an angle with respect to a reference axis passing the reference point. When the figure to be detected is an ellipse, a contour point of the ellipse may be used as a characteristic point, and an elliptical center may be used as the reference point.
Plural inspecting points Pj (j=1 to N, N represents a natural number) located on the contour of the figure are extracted from the input image. This inspecting point Pj is represented by an orthogonal coordinate system (Xj, Yj) set on the input image. Further, these orthogonal coordinates (Xj, Yj) are transformed by using Formulas F1 and F2. In these formulas, θ shows an inclination of the template figure.Xj=X+Ri×cos(αi+θ)  (F1)Yj=Y+Ri×cos(αi+θ)  (F2)
In this coordinate transformation, it is supposed that inspecting point Qj=(Xj, Yj) corresponds to characteristic point Pi=(Ri, αi) shown in the template, and the position of the reference point on the input image is calculated. Accordingly, if inspecting point Qj is fixed and the coordinate transformation is performed with respect to all the polar coordinate vectors enumerated in the table, a locus of reference point candidature is calculated. In particular, when θ is fixedly considered, the locus of this reference point candidature becomes the same shape as the template.
Namely, as shown in FIG. 12, plural loci 21 of the reference point candidature are calculated by executing similar coordinate transformation with respect to plural inspecting points Qj. A spot overlapped at one point with respect to all these plural loci 21 becomes the reference point 23 of the figure to be detected. Dotted line 20 in FIG. 12 shows an ellipse as the figure of an inspecting object, and point 22 shows inspecting point Qj.
When the position of the ellipse is detected by only the generalized Hough transform from the input image including a figure having the contour having defects as the ellipse as shown in FIGS. 11A and 11B, the position of the ellipse is presumed by using an inspecting point on the contour including these defects. Therefore, a problem exists in that detection accuracy of this position of the ellipse is greatly reduced. Here, the position of the ellipse is the position of a contour point of the ellipse determined by the ratio of major and minor axes, an inclination (i.e., an angle of the major axis) of the major axis, etc.
Therefore, the driver's eyes and behavior cannot be exactly detected from the image (i.e., the input image) including the face of the driver. Accordingly, a problem exists in that no control of driver support, etc. according to a situation of the driver can be performed.
Further, in an image in which the circumference of a driver's eye is photographed by a camera fixed into a vehicle as shown in FIGS. 11A and 11B, the size and shape of the driver's eye (iris or eye pupil) shown within this image, i.e., the size (the length of a major axis) of an ellipse to be detected, a ratio of the major and minor axes of the ellipse and an inclination (an inclination angle of the major axis) of the ellipse are variously different in accordance with a seating position of the driver and a direction of the face of the driver.
For example, in a case in which the ellipse of a template and the ellipse of an input image are the same in inclination θ but are different in size as shown in FIG. 19A, and a case in which the ellipse of the template and the ellipse of the input image are the same in size but are different in inclination θ as shown in FIG. 19B, no locus 25 is overlapped at one point and the center (reference point) of the ellipse is not detected. However, a dotted line 27 in FIGS. 19A and 19B is the ellipse as a figure of an inspecting object, and a point 26 is an inspecting point Qj.
Thus, when it is intended to detect the ellipse not constant in size and shape by the generalized Hough transform, it is necessary to prepare the template every ellipse different in the ratio of the major and minor axes. Further, when coordinate transformation is performed, it is necessary to change θ of formulas F1 and F2 in consideration of the inclination of the ellipse, and enlarge/reduce the template in size in consideration of the size (the length of the major axis) of the ellipse. Therefore, a problem exists in that a processing amount until the detection of the center of the ellipse becomes enormous.
In particular, it is required that a processor mounted to a vehicle for image processing is cheap and is excellent in noise resisting property. Therefore, no sufficiently high speed processor can be used. Therefore, when the generalized Hough transform is used in the detection of the iris or the eye pupil in the vehicle mounting controller for detecting the iris or the eye pupil of the driver and performing driver's support, etc. on the basis of its detecting result, a problem exists in that delay is caused in control and no structure resisting a practical use can be realized.